Complexity reduction for vehicular channel estimation using the filter-divergence measure

In vehicular communications systems the channel estimation filter suppresses the additive noise in channel estimates obtained from pilot symbols. Vehicular channels show local stationarity for a finite region in time and frequency, only. Such a process can be divided into consecutive stationarity regions, allowing to calculate a Wiener filter. We analyze the increase of the mean square error (MSE) when using a mismatched Wiener filter calculated for a past stationarity region. The MSE increase of the filter is related to a new metric, the filter divergence directly observable at the receiver side. By accepting an increase of MSE, measured by the filter-divergence, the same filter coefficients can be used for several stationarity regions,... (More)

In vehicular communications systems the channel estimation filter suppresses the additive noise in channel estimates obtained from pilot symbols. Vehicular channels show local stationarity for a finite region in time and frequency, only. Such a process can be divided into consecutive stationarity regions, allowing to calculate a Wiener filter. We analyze the increase of the mean square error (MSE) when using a mismatched Wiener filter calculated for a past stationarity region. The MSE increase of the filter is related to a new metric, the filter divergence directly observable at the receiver side. By accepting an increase of MSE, measured by the filter-divergence, the same filter coefficients can be used for several stationarity regions, allowing computational complexity reduction in a real system. (Less)

@misc{7efeddac-3e17-4722-9491-07a178fb9acc,
abstract = {In vehicular communications systems the channel estimation filter suppresses the additive noise in channel estimates obtained from pilot symbols. Vehicular channels show local stationarity for a finite region in time and frequency, only. Such a process can be divided into consecutive stationarity regions, allowing to calculate a Wiener filter. We analyze the increase of the mean square error (MSE) when using a mismatched Wiener filter calculated for a past stationarity region. The MSE increase of the filter is related to a new metric, the filter divergence directly observable at the receiver side. By accepting an increase of MSE, measured by the filter-divergence, the same filter coefficients can be used for several stationarity regions, allowing computational complexity reduction in a real system.},
author = {Bernadó, Laura and Zemen, Thomas and Paier, Alexander and Kåredal, Johan},
language = {eng},
title = {Complexity reduction for vehicular channel estimation using the filter-divergence measure},
year = {2010},
}